Overview
WaveNet, yakaunzwa neDeepMind muna 2016, yaive budiriro neural network iyo inogadzira yakasvibira odhiyo sampu imwe panguva, ichigadzira zvinoshamisa kutaura kwechisikigo uye mimhanzi. Yakaisa chiyero chemazuva ano chepamusoro-kutendeseka mavara-ku-kutaura.
WaveNet inogara muodhiyo-AI workflows inoshandura kutaura, mimhanzi, uye ruzha rwekutaurirana, kuwanikwa, uye kugadzirwa kwenhau.
Deep Dive
WaveNet ndeye autoregressive generative modhi: inofanotaura yega yega odhiyo sampu yakamisikidzwa pane ese masampuli pamberi payo, kazhinji pagumi nematanhatu kana 24,000 masampuli pasekondi. Yayo musimboti innovation is a stalk of dilated causal convolutions. Causal zvinoreva kuti modhi inongotarisa kumashure munguva, ichichengetedza kurongeka kwechizvarwa; dilation zvinoreva kuti imwe neimwe nhanho inosvetukira kuwedzera kukura kwemasampuli, saka ine mwero stack inovhara zviuru zvemasamples (munda wakafara unogamuchira) pasina mutengo wakakura. Yakamisikidzwa pamhando dzemitauro kana mel-spectrogram, WaveNet inogadzira kutaura kwakaringana kupfuura iyo concatenative uye parametric manzwi akatangira, ichivhara yakawanda yegeji kune zvakarekodhwa zvevanhu uye kusimbisa ekutanga shanduro dzeGoogle Mubatsiri.
Technical Insight
Dilated convolutions ndiyo dhizaini yakakosha: ine dilation rates ye1, 2, 4, 8, zvichingodaro, network chete makumi ematanho akadzika anogona kuenda kuzviuru zvemasamples apfuura, achitora zvese zvakanaka waveform ruzivo uye kureba kweprosodic chimiro. Iwo anobuda mamodheru kukosha kwesample yega yega sekugoverwa kwechikamu (pakutanga mazinga mazana maviri nemakumi mashanu nenhanhatu kuburikidza ne-mu-mutemo kuenzanisa), uye gedhi activation units pamwe neasara uye skip zvinongedzo zvinodzikamisa kudzidziswa kweiyi stack yakadzika.
Kudzidzira WaveNet
WaveNet, yakaunzwa neDeepMind muna 2016, yaive budiriro neural network iyo inogadzira yakasvibira odhiyo sampu imwe panguva, ichigadzira zvinoshamisa kutaura kwechisikigo uye mimhanzi. Yakaisa chiyero chemazuva ano chepamusoro-kutendeseka mavara-ku-kutaura. WaveNet inogara muodhiyo-AI workflows inoshandura kutaura, mimhanzi, uye ruzha rwekutaurirana, kuwanikwa, uye kugadzirwa kwenhau. Kuti uvake kunzwisisa kwakadzama, bata WaveNet semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodiwa, kujekesa fungidziro, uye patsanura izvo zvingaitwe nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa WaveNet zvinobata mhando, latency, uye mvumo sezvikamu zvakakosha zvakaenzana zvehurongwa hwekuendesa. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza. Panguva imwecheteyo, kusashandiswa kweIzwi zvisizvo uye njodzi dzekuedzesera dzinowedzera kana chibvumirano chisipo. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza.
Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zveMedia zvinogona kutumira odhiyo yakakwenenzverwa nekukurumidza nemabhajeti madiki.
Zvikwata zveMedia zvinogona kutumira odhiyo yakakwenenzverwa nekukurumidza nemabhajeti madiki. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Masisitimu anotarisana nevatengi anogona kugadzirisa kutaurirana kwekutaura pamwero mukuru.
Masisitimu anotarisana nevatengi anogona kugadzirisa kutaurirana kwekutaura pamwero mukuru. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Kugadzira manzwi anonzwika e Google Mubatsiri uye Google Cloud Zvinyorwa-ku-Kutaura
Kuita seneural vocoder inoshandura mel-spectrograms kuita waveforms mumapaipi eTTS seTacotron 2.
Kubatanidza piyano chaiyo uye mimhanzi yezviridzwa kubva kune yakaomeswa odhiyo
Inzwi synthesis yezvishandiso zvekuwanikwa uye kurondedzera kweaudiobook
Maitiro Ekuita
WaveNet mukuita
Kugadzira manzwi anonzwika eGoogle Mubatsiri uye Google Cloud Text-to-Speech.
Kugadzira manzwi echisikigo eGoogle Mubatsiri uye Google Cloud Text-to-Speech Teams vanowanzowana mibairo iri nani kana vachinge vatsanangura zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa pakubudirira uye kukanganisa mutengo nekufamba kwenguva.
WaveNet mukuita
Kuita seneural vocoder inoshandura mel-spectrograms kuita waveforms mumapaipi eTTS seTacotron 2.
Kuita seneural vocoder inoshandura mel-spectrograms kuita waveforms mumapaipi eTTS seTacotron 2 Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
WaveNet mukuita
Kubatanidza piyano chaiyo uye mimhanzi yezviridzwa kubva kune yakaomeswa odhiyo.
Kubatanidza piyano yechokwadi uye mimhanzi yezviridzwa kubva kune yakasvibira odhiyo Matimu anowanzo kuwana mhedzisiro iri nani kana vachitsanangudza zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye tarisa zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
WaveNet mukuita
Inzwi synthesis yezvishandiso zvekuwanikwa uye redhiyo bhuku kurondedzera.
Inzwi synthesis yezvishandiso zvekuwanikwa uye odhiyo bhuku rekutaura Matimu anowanzo kuwana zvirinani mhedzisiro kana vachitsanangudza zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kusashandisa izwi zvisizvo uye njodzi dzekuedzesera dzinowedzera kana chibvumirano chisipo.
Kururama kunogona kudonha mumitauro, mataurirwo, kana nharaunda dzine ruzha.
Synthetic audio inogona kukanganisa kutaura kwechokwadi isina mavara akajeka.
Implementation Roadmap
Wana mvumo yakajeka yekutora inzwi, kugadzira, uye kushandisa zvakare.
Wana mvumo yakajeka yekutora inzwi, kugadzira, uye kushandisa zvakare. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Yedza mhando pavatauri vakasiyana uye mamiriro ekumashure.
Yedza mhando pavatauri vakasiyana uye mamiriro ekumashure. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tsanangura apo munhu anofanira kuongorora kana kubvumidza zvabuda.
Tsanangura apo munhu anofanira kuongorora kana kubvumidza zvabuda. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Label synthetic odhiyo uye chengetedza marekodhi ekuzvidavirira.
Label synthetic odhiyo uye chengetedza marekodhi ekuzvidavirira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.